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Poster Abstracts

Marie-Josèphe Amiot-Carlin & Marlene Perignon

Title: Modeling and intervention studies to promote nutritional security and sustainable diets

Authors: Marlene Perignon1, Marie-Josèphe Amiot-Carlin1, Nicole Darmon1

1Unité Mixte de Recherche “Nutrition, Obesity and Risk of Thrombosis” Institut National de la Recherche Agronomique 1260 INRA, Institut National de la Santé et de la Recherche Médicale 1062 INSERM, Aix- Marseille Université, F-13385, Marseille, France


Ensuring food security requires to promote sustainable diets, namely nutritionally adequate, culturally acceptable, economically affordable and with low environmental impact, in the various contexts of industrialized and developing countries. Through different projects based on modeling or intervention studies, our team aims to optimize food consumptions to tend towards sustainable diets. The approach used is first to evaluate nutritional adequacy, environmental impact and cost of current eating and food provisioning habits, and then to identify food changes needed to reach sustainability.

MEDINA project “Promoting sustainable Mediterranean food systems for good nutrition and health”: by analyzing food consumption in three contrasted areas in Tunisia and the south of France, this project aims to promote sustainable food systems in the Mediterranean zone. (

SUSDiet project “Implementing sustainable diets in Europe”: based on the analysis of various consumption patterns from North to South of Europe and through the modeling of diets and their health and environmental impacts, this project aims to define the most sustainable dietary targets to be promoted for European consumers.

AVASUN project “Taking into account Nutrient Bioavailability for Sustainable diets”: starting from food consumption of French adults, this project aims to assess the compatibility between reducing the environmental impact of diet and fulfilling nutritional recommendations, while taking into account nutrient bioavailability.

OPTICOURSES project: by analyzing actual food purchases, this intervention study acts on both the demand and the supply to improve the nutritional quality/price ratio of the food purchases of consumers facing financial issues. (

Our team is also involved in the incubation step of the metaprogramme GloFoodS launched by INRA-CIRAD and focusing on the transitions for global food security through integrated and cross-disciplinary approaches. (

Jon Arthur

Resilience, Risk and Reason in Global Fast Moving Consumer Goods Supply Chains.

John Arthur & Louise Moody

Global Fast Moving Consumer Goods companies are a critical player in the food chain. Such companies harness increasingly dynamic supply chains to meet their competitive objectives on variables such as cost, flexibility and availability of key raw materials. Despite the inherent and obvious complexity of such supply chain design activity, companies display a very poor appetite for complexity in risk modelling around the resilience of these supply chains.

This poster examines the successful application of a heuristic risk modelling tool to increase supply chain resilience. Improved rationality and transparency of the risk cost benefit trade off needed to protect a global supply chain is achieved by harnessing the “natural reference grammar” of the pre-existing decision processes. Thus the tool is an example of a “for experts system”. Through a modified Bayesian paradigm this supports complexity reduction in real-time, multi-agency, high-pressure, distributed decision making for supply chain risk.

The real world trade-off between system efficacy and decision model accuracy is reviewed in terms of the perceived utility, experienced usability and overall technology transfer of increased decision making rationality. The implications for secure and fair global supply chains in the long term is discussed.


Martine Barons

Towards a decision support system for UK food security

Building on recent theoretical advances in combining expert judgement for decision support, this poster will outline advances in a Dynamic Bayesian Network implementation for food security decision support for UK policymakers.


Sebastian Fairhead

Translating UK-India research into improved brassica food production


Franziska Gaupp

Correlated crop yield losses in global “breadbaskets”

With a focus on global food security, my study will look at crop yield losses in different regions and investigate globally correlated yield losses caused by droughts. Looking at past crop yield losses in different regions of the world in a short time-span and their joint effects such as price spikes on the world grain market show clearly that it is important to understand correlated extreme events. Especially under climate change, there is a need to investigate the probabilities of correlated yield losses due to droughts.

This study focuses on the modelling of crop yield losses. Numerous papers have found a correlation between large-scale circulation indices such as the North Atlantic Oscillation (NAO) or the El Niño-Southern Oscillation (ENSO) and droughts as well as crop yield deviations. These correlations will help us to identify a global dependence structure of yield losses. First, for each major crop producing area (“breadbasket”) production losses are investigated. Then, a global dependency structure of yield losses will be identified by linking the probability distribution of yield losses in one breadbasket with the probability distribution in another breadbasket using the copula methodology. Copulas are functions which combine univariate distribution functions in order to form multivariate distribution functions. The copula method is a flexible tool as it allows marginal distributions from different families to describe and to model dependence between random variables. In that way, the probability of a joint occurrence of yield losses in different breadbaskets in the same year can be derived.


Alex Kharlamov

Some case based research on food supply chains. More specifically how segmentation can be used to improve SC effectiveness & efficiency


Grace Kwong

Title: Bayesian analysis of PRRS virus spread in Ontario swine herds

Porcine reproductive and respiratory syndrome (PRRS) has a worldwide distribution. This economically important endemic disease causes reproductive failure in breeding stock and respiratory tract illness in young pigs. In Ontario restricted fragment length polymorphism (RFLP) 1-18-4 has been determined as one of the most common virus genotypes.

Individual-level models (ILMs) for infectious diseases, fitted in a Bayesian MCMC framework, have been used to describe both the spatial and temporal spread of diseases. They are an intuitive and flexible class of models that can take into account population heterogeneity via various individual-level covariates. The objective of this study is to identify relative importance of risk factors for the spread of the genotype 1-18-4 from monitoring data in
southern Ontario using ILMs. Specifically, we explore networks through which resources are obtained or delivered, as well as the ownership structure of herds, and identify factors that may be contributing to high risk of infection.
A population of 316 herds which experienced their PRRS outbreaks between September 2004 and August 2007 are included in the analyses, in which 194 (61%) are sow herds. During the study period, 45 herds (27 sow herds) experienced their first outbreak due to RFLP 1-18-4. Our results show that the three relatively most important factors for the spread of 1-18-4 genotype in Ontario swine herds were sharing the same herd ownership,
gilt source and market trucks. All other networks had relatively smaller impact on spread of this PRRSV genotype. Spatial proximity could not be identified as important contributor to spread. Our findings also suggest that gilt acclimation should be practiced whenever possible and appropriate to reduce the risk for the herd and for others as it is already widely implemented and recommended in the North American swine industry.


Manuele Leonelli

A Bayesian Decision Support System for a Multi-Expert Distributed Decision Analysis

Complex decision support systems often consist of component modules which, encoding the judgments of panels of domain experts, describe a particular sub-domain of the overall system. Ideally these disparate modules need to be pasted together to provide a comprehensive picture of the whole process. The challenge of building such an integrated system is that, whilst the qualitative features are common knowledge to all, the explicit forecasts and their associated uncertainties are expressed only locally. The structure of the integrated system therefore needs to facilitate the coherent piecing together of these separate evaluations. If such a system is not available there is a serious danger that this might drive to incoherent and so indefensible decision making. With this work we develop a graphically based framework which embeds a set of conditions that, if satisfied in a given context, are sufficient to ensure the composite system is truly coherent. Furthermore, we develop new message passing algorithms that enable the uncertainties within each module to be fully accounted for in the evaluation of expected utility scores of this composite system.

Irene Monasterolo

Tbc: Analysis characteristics of systemic risk in the food system in relation to resource access, political instability and climate change

Razvan Romanescu

Modelling the spread of two strains of disease via aggregate-level infectivity curves

Well formulated models of disease spread, and efficient methods to fit them to observed data, are powerful tools in the surveillance and control of infectious diseases. Our project considers the problem of the simultaneous spread of two related strains of disease in a context where spatial location is the key driver of disease spread. The starting point in modeling are the Individual Level Models (ILMs) of disease transmission introduced by Deardon et al. (2010). We extend these models to accommodate the competing spread of the pathogens in a two-tier hierarchical population (e.g. one consisting of farms and animals).

We also present a framework for speeding up the computationally intensive process of fitting the ILM to data, typically done using Markov chain Monte Carlo (MCMC) in a Bayesian framework, by turning the inference into a two-stage process. At the farm level, we approximate the number of animals infected over time by infectivity curves, which are fit via maximum likelihood estimation to data sampled from farms. Inference then proceeds using Bayesian MCMC for the remaining parameters. Finally, we use posterior predictive distributions of salient epidemic summary statistics, in order to assess the model fit.


Carla Sarrouy

Food security and the limitations of the neo-liberal approach to agriculture: a case study of Senegal

C. Sarrouy & R.D. Lillywhite Warwick Crop Centre, University of Warwick, United Kingdom

The Green Revolution which focused on the improvement of crops, chemical inputs and mechanisation to increase agricultural yields was an attempt to address concerns over the availability of food (Patel, 2012). It was based on neo-liberal ideals and focused on increasing the yield of key crops in Asia and Latin America. The Green Revolution succeeded in increasing the global crop production and benefited a small number of large seed and chemical companies but it also introduced burdens on farmers in poorer and developing countries and resulted in environmental degradation and debt (Shiva, 1991). The approach has been strongly criticised by many researchers and farmer movements who highlight the importance of addressing all the components of food systems to fight food insecurity (Holt-Giménez and Altieri, 2012). Agroecology defends a food systems approach, by considering the entire food chain from consumption to waste management and social, economic and environmental aspects of food.

This poster reports on a study of food insecurity in Senegal, which serves as a case study of a country where neo-liberal initiatives have failed and contributed to increased national vulnerability and food dependency.


Complex food systems: an alternative approach to understanding food security

C. Sarrouy & E. Uprichard, Warwick Crop Centre & Centre for Interdisciplinary Methodologies, University of Warwick, United Kingdom

This poster proposes an alternative methodological programme of food security research. It does this by drawing on key oversimplifications conveyed in food security research as illustrative examples of some of the main ways in which issues of causality and subsequent solutions are presented. An illustrative oversimplification discussed in this paper is the idea that food insecurity, and ultimately hunger, are issues caused by insufficient food production. The poster will draw on such examples as a way of presenting the problems of simple causality intrinsic to such accounts. In turn, the strengths and benefits of a complex systems approach to the same problems will also be conveyed.


Tbc : Mapping the food initiatives in Coventry

C. Sarrouy, Moya Kneafsey & Colin Anderson


Craig R. Shenton

The Effect of Export Restrictions on Global Food-Commodity Markets: A Network Data Analysis

Craig R. Shenton1, David J.B. Lloyd2, and Angela Druckman1

1Centre for Environmental Strategy, University of Surrey, Guildford, GU2 7XH, UK 2Department of Mathematics, University of Surrey, Guildford, GU2 7XH, UK

The global trade in food-commodities creates a complex network of interdependent supply chains. As more countries become reliant on this network of trade, the more vulnerable it becomes to systemic risks and shocks. Evidence suggests that export restrictions played a key role in recent episodes of extreme food-price volatility, which had a devastating impact on the affordability and availability of food to the world’s most vulnerable populations. In this study, we build on previous research which has shown that a country’s susceptibility to similar economic events is directly related to its level of integration into the trade networks structure (or topology). Understanding the network structure of trade can therefore, be seen as a crucial element in understanding food security. Informed by a network theory approach,

We analyse UN Comtrade data detailing 70,000 transactions in three major food-commodity markets (Wheat, Rice, and Maize) over the period 2000-2012. We estimate the rate at which food-importing countries are affected by export restrictions and model this as a Poisson process, with the mean rate increasing as a function of degree (i.e., the number of trade links connected to or from that country). Using this, we create a composite risk index for each food-commodity market and find that, generally, countries with the highest degrees have the lowest supply risk. We interpret our results in terms of developing a policy of strategic reserves to mitigate these risks.

Daniel Simpson

Tbc Bats….

Andy Tock

Home-grown haricot: cultivating an idea…

Eric B. Holub1, Guy C. Barker2 and Andrew J. Tock1

1Warwick Crop Centre, University of Warwick, Wellesbourne Campus, CV35 9EF

2School of Life Sciences, University of Warwick, Gibbet Hill Campus, CV4 7AL

Common bean (Phaseolus vulgaris L.) is a staple source of gluten-free protein, low glycaemic-index carbohydrate, fibre and micronutrients for direct consumption in the human diet. The nutritional value of beans as a component of a balanced, healthy human diet is recognised for promoting associated health benefits, such as helping to prevent cancer, diabetes and heart disease, as well as lowering cholesterol.

Common bean is the main ingredient in a British favourite comfort food, (haricot) beans-on-toast. The haricot bean is not currently grown in this country; the UK consumer depends entirely on imports of dry common beans of all market classes. The haricot bean is nonetheless a potentially viable rotation crop for UK farmers, and home-grown beans could be attractive to people in Britain.

This research builds on work done by crop scientists at the National Vegetable Research Station in Wellesbourne (now the University of Warwick Crop Centre). They were adapting haricot bean for UK growing conditions. The current project is aimed at developing modern genetics and genomics tools to accelerate the process of adapting varieties to the UK climate. It is anticipated that this project will eventually have an impact in providing UK farmers with a novel, short-season, legume break crop that would promote soil renewal and aid grass-weed control, and ultimately establishing a food supply chain for haricot beans in the UK, providing consumers with a nutritious source of home-grown vegetable protein.